Advancement of the digitalization in image devices and development of network technology particularly in the Internet promote popularization of a cross-media-system. This system allows arbitrary exchanging of image information by coupling various image devices, (such as a scanner, printer and display) with each other on an open system. Businesses such as E-commerce and Telemedicien medical service requiring strict color reproduction have taken off thanks to this system.
The open system uses various devices in various viewing environments. There is a demand for color management systems (CMS), i.e., software and hardware, which are independent of both the device colorimetric characterization and viewing environments and allow color reproduction of a certain quality.
A camera or a scanner (a source device) should deliver the color information it takes in to the open system exactly. On the other hand, a display or a printer (an output device), which outputs the color information it receives, should render the information exactly.
For instance, when a camera takes in color information exactly, if a display processes the information inadequately, then the exact color information cannot be displayed. An accuracy of color reproduction by this entire system is thus lowered.
For instance in E-commerce via the Internet, a customer views goods on a display in different colors from actual ones.
However, when a color displayed area (gamut) taken by a source device is larger than the gamut of an output device, the source device should change the color information to fit within the gamut of the output device. This manipulation is referred to as “mapping.” The color outside the color gamut of the output device cannot be reproduced; however, when a color image is reproduced, an image painted by colors as close as possible to the original image is required. Therefore, gamut mapping should be optimized, so that a reproduced image appears as natural as possible.
In the color management system (CMS), the following elements should be optimized because color information must be exchanged correctly between different image devices as well as viewing environments:                (1) Input/output characteristics (relation between values of device-driving-signal and colorimetric values) of respective image devices is standardized.        
The principle of the CMS is to establish input/output characteristics, i.e., a relation between a video signal (e.g. RGB signals) driving an image device and colorimetric value (e.g. CIEXYZ of XYZ display system or CIELAB of L,a,b, display system, both of which are authorized by Commission International de I' Eclairage (CIE)). Then the colors from the source device are converted into device-independent color data so that any device can handle the color data through a given procedure. Then first of all, the input/output characteristics of the input/output devices linked to an open system should be standardized.
International Electrotechnical Commission (IEC) is modeling the input/output characteristics of image devices such as an LCD, PDP, scanner, digital camera, and printer, and is drafting a standard specification.                (2) Input/output characteristics of viewing-environment-dependent visual system are standardized.        
Tri-stimulus value of CIEXYZ is a psychophysical quantity produced by multiplying a physical quantity of light and a spectral-response characteristic of human eyes (when it is expressed with a wave-length function, it is referred to as color matching function). Two colors having the same XYZ thus appear the same. However, when the color matching function—expressing spectral-response characteristic of the human eyes—changes depending on viewing environments and human chromatic adaptation is in different viewing environments, the two colors having the same XYZ may appear differently. This phenomenon is referred to as, in general, “different color appearance.” An objective of the CMS is to reproduce, in any viewing environment, the color the output device receives as a color appearance which is the same as the color information the source device sent out.
It is thus necessary to standardize the influence of viewing environment which the input/output characteristics of a human visual system is subjected to in order to find a counterpart color (corresponding color) of the color XYZ which appears the same under a different lighting condition on a source device and an output device.
The CIE specified a color appearance model CIECAM97s in TCI-34 (Testing Color Appearance Models, Report on CIECAM97s, April 1998) where the model considers the brightness of background and the XYZ values of a white point influencing the human chromatic adaptation.                (3) Gamut mapping is optimized.        
A method is studied to send out color information by compressing the entire gamut of a source device in order to fit the gamut within a smaller gamut of the output device.
Many engineers have proposed various methods of gamut compression, and the CIE is now trying to standardize the method.
Regarding the method of gamut compression, GCUSP developed by Jan Morovic has been well known; however, this method has the following problems: The GCUSP is a gamut compression method to minimize the lowering of chroma, however, it does not consider the three attributes of color reproduction comprehensively, i.e., lightness, chroma and hue after performing the gamut mapping. The color reproduction does not solely depend on chroma but the lightness and hue are also the critical factors.
The method of gamut compression cannot reproduce the same color as a color appearance or colorimetric value when a source device has a different gamut from an output device. As a result, a problem occurs that an agreement between colorimetric values or color appearances cannot be applied to as a design target.
A method of agreeing the color appearances is studied. One effective method is to control colors based on an agreement of color names.
When the gamut mapping is performed, it is impossible to render the same colors on respective devices, thus it will be a target to exchange color information between respective devices in order to show the difference in overall image as little as possible.
To achieve this target, a concept of categorical color perception is introduced. A human being has an ability of perceiving a color and another ability of grouping some colors into a color category. For instance, ‘light green’, ‘dark green’ and ‘bluish green’ appear to be different when they are placed sequentially; however they are grouped into one category ‘green’.
If a red flower on a CRT display is printed ‘a red flower’ in the same category on a sheet of paper, viewers do not mind subtle differences and get an impression that the two images are the same; however, when it is printed in a different color category such as ‘a yellow flower’ or ‘a flower of orange color’, the viewers get an impression that the two images are different.
Further, when a flower's red has more intensity than an apple's red on a CRT, it is preferable to see the flower's red with more intensity than the apple's red on a printed matter, and it is not preferable to see the flower's red with less intensity than the apple's red.
It is effective to exchange color information thereby agreeing color names between a source device and an output device, and yet, preserving a perceptive quantity relation of a color such as chroma and the like in order to minimize a difference of entire images in gamut mapping.
Consider colors having a color difference between two points existing in a color space of a source device. When the color difference is strictly preserved and the two colors are mapped in an output device, the difference of the two colors from the viewpoint of the color difference is the same on the source device and the output device. However, when a color categorical control is not built in the CMS, the two colors in the same color category on the source device may be mapped at the spots striding over a boundary between color categories and reproduced in two colors having different color names.
A method of color adjustment based on an agreement of color names is disclosed in Japanese Patent Application Non-examined Publication No. H08-191400. This method is manipulated by an operator when he or she adjusts a color rendered on a display so that the color can agree with a given name of a target color.
To be more specific, the colorimetric value of each pixel of an image is expressed in lightness (L), chroma (C) and hue (H) in a polar coordinate system. Then the differences of each element between a reference color and a target color, i.e. ΔL, ΔC and ΔH are added to the color before adjustment, and the color after adjustment is obtained. Among the colors after adjustment, the color having color names different from those of target colors are re-adjusted with respect to the differences ΔL, ΔC and ΔH. In re-adjusting, ΔL/n, ΔC/n and ΔH/n are used (n: numeral around 10). If the re-adjustment cannot find the agreement with the color name of the target color, the method changes the ‘n’ and repeat the adjustment of the differences until the color name finds the agreement.
However, the color adjustment method discussed above has still have the following problems:
First, differences of ΔL, ΔC and ΔH are changed repeatedly on a trial and error basis until the color name find the agreement. This procedure incurs increased work time, and yet, an image after the adjustment tends to be dispersed.
Second, the names of colors adjusted with the differences of ΔL, ΔC and ΔH differ from those of the target colors, and they are re-adjusted with the differences of ΔL/n, ΔC/n and ΔH/n. In this case ‘n’ is determined by a trial and error process. The trial and error process incurs increased work time, and the image after the adjustment is vulnerable to dispersion. Further, when a plurality of adjusted colors are available, determining ‘n’ by trial and error may reverse the positions of the adjusted colors in color space, or produce a color-skip. These phenomena are viewed as a pseudo outline and degrade the color reproducibility.